An approach of battery control has focused on model-based state of charge estimation, power capability calculation, battery health management (power and capacity fade) as well as cell balancing. Model-based battery controls (state of charge, state of health, and state of power (power capability)) refer to closed-loop systems which use prediction/correction type algorithms in parameter and/or state estimation. In prediction/correction type algorithms, an internal model for the battery is used to first predict the state variables and then predict the outputs. The predicted outputs are compared with the real, measured outputs. The resultant projection errors are used to compensate for predicted state variables to obtain a final state estimation. This approach may be used in recursive parameter identification, state observation, among others.
Questions such as the following should be answered before a model-based battery control can be used with confidence: Is the closed loop system reasonably guaranteed to be stable? What actions should be taken if the closed loop system becomes unstable? Is the performance of the closed loop system reasonably guaranteed to be good? What actions should be taken if the closed loop system does not perform properly?